让框选抠图恢复原任务并回填画布
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@ -1,100 +1,15 @@
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import { NextRequest, NextResponse } from "next/server";
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import { NextResponse } from "next/server";
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import { auth } from "@/app/(auth)/auth";
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import {
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BoxCutoutServiceError,
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executeBoxCutoutJob,
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} from "@/lib/ai/box-cutout/service";
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import { RmbgServiceError } from "@/lib/ai/rmbg/service";
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import { getPointsSystemConfig } from "@/lib/db/queries";
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import { prepareFeaturePointsCharge } from "@/lib/points/feature-charge";
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import { getImageToolCreditCost } from "@/lib/points/config";
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import { executeBoxCutoutPOST } from "@/lib/canvas/operations/box-cutout";
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export const runtime = "nodejs";
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export const maxDuration = 60;
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type BoxCutoutRequest = {
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imageUrl?: string;
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cropRect?: {
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x?: number;
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y?: number;
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width?: number;
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height?: number;
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};
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paddingRatio?: number;
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prompt?: string;
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chatId?: string | null;
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messageId?: string | null;
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skipGallerySave?: boolean;
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sourceNodeId?: string;
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};
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export async function POST(request: NextRequest) {
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try {
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const session = await auth();
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if (!session?.user?.id) {
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return NextResponse.json({ success: false, error: "未授权，请先登录" }, { status: 401 });
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}
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const body = (await request.json()) as BoxCutoutRequest;
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const rawImageUrl = String(body.imageUrl || "").trim();
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if (!rawImageUrl) {
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return NextResponse.json({ success: false, error: "缺少 imageUrl 参数" }, { status: 400 });
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}
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const resolvedImageUrl = new URL(rawImageUrl, request.url).toString();
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const pointsConfig = await getPointsSystemConfig();
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const pointsCharge = await prepareFeaturePointsCharge({
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userId: session.user.id,
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unitCost: getImageToolCreditCost(pointsConfig, "box-cutout"),
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reason: "image_box_cutout",
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modelId: "box-cutout",
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note: "框选抠图消耗积分",
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pointsConfig,
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});
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if (!pointsCharge.ok) {
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return NextResponse.json(pointsCharge.payload, { status: pointsCharge.status });
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}
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const result = await executeBoxCutoutJob({
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userId: session.user.id,
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imageUrl: resolvedImageUrl,
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cropRect: body.cropRect || {},
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paddingRatio: body.paddingRatio,
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prompt: body.prompt || "框选抠图",
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chatId: body.chatId || null,
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messageId: body.messageId || null,
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skipGallerySave: body.skipGallerySave === true,
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sourceNodeId: body.sourceNodeId,
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});
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if (pointsCharge.chargeable) {
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try {
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await pointsCharge.consume();
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} catch (pointsError) {
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console.error("[Points] Failed to consume box cutout points:", pointsError);
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}
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}
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return NextResponse.json(result);
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} catch (error) {
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if (error instanceof BoxCutoutServiceError || error instanceof RmbgServiceError) {
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return NextResponse.json(
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{
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success: false,
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error: error.detail || error.message,
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},
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{ status: error.status },
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);
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}
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console.error("[BoxCutout] 处理失败:", error);
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return NextResponse.json(
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{
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success: false,
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error: error instanceof Error ? error.message : "框选抠图失败",
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},
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{ status: 500 },
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);
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export async function POST(request: Request) {
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const session = await auth();
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if (!session?.user?.id) {
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return NextResponse.json({ success: false, error: "未授权，请先登录" }, { status: 401 });
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}
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return executeBoxCutoutPOST(request, session.user.id);
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}
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@ -4683,106 +4683,44 @@ export function ImageNode({
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return;
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}
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setIsCreatingDetachedResultNode(true);
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if (!projectId || !runCanvasRemoteOperation) {
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toast.error("画布还在加载，请稍后再试");
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return;
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}
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setIsCreatingDetachedResultNode(false);
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setIsProcessing(true);
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const actionName = "框选抠图";
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const newNodeId = addNode({
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type: "image",
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position: {
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x: node.position.x + node.size.width + 20,
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y: node.position.y,
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},
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size: { width: node.size.width, height: node.size.height },
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data: {
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src: "",
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status: "generating",
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prompt: `${actionName}处理中...`,
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title: `${displayTitle}-${actionName}`,
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originalSrc: data.src,
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metadata: {
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cropRect: boxCutoutSelection,
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paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
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},
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},
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connections: [node.id],
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});
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try {
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const result = await imageGenerationService.boxCutout({
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imageUrl: data.src,
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cropRect: boxCutoutSelection,
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paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
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sourceNodeId: node.id,
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});
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if (result.success && result.data?.url) {
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updateNode(newNodeId, {
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data: {
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src: result.data.url,
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status: "completed",
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prompt: `${actionName}结果`,
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title: `${displayTitle}-${actionName}`,
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originalSrc: data.src,
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metadata: {
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cropRect: boxCutoutSelection,
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cropRectApplied: result.data.cropRectApplied,
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paddedCropRectApplied: result.data.paddedCropRectApplied,
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paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
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editMode: "box-cutout",
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},
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},
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});
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toast.success(`${actionName}完成`);
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} else {
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updateNode(newNodeId, {
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data: {
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src: "",
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status: "failed",
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prompt: `${actionName}失败`,
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title: `${displayTitle}-${actionName}-失败`,
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originalSrc: data.src,
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metadata: {
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cropRect: boxCutoutSelection,
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paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
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},
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},
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});
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toast.error(result.error || `${actionName}失败`);
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}
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} catch (error) {
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console.error("框选抠图失败:", error);
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updateNode(newNodeId, {
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data: {
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src: "",
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status: "failed",
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prompt: `${actionName}失败`,
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title: `${displayTitle}-${actionName}-失败`,
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originalSrc: data.src,
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metadata: {
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cropRect: boxCutoutSelection,
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paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
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},
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const command = createCanvasCapabilityClientCommand({
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capabilityId: "image.box_cutout",
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nodeIds: [node.id],
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projectId,
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source: "toolbar",
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args: {
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...boxCutoutSelection,
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paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
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},
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});
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toast.error(`${actionName}失败，请重试`);
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await runCanvasRemoteOperation(() => executeCanvasToolbarCapability(command));
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toast.success(`${actionName}完成`);
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} catch (error) {
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console.error("框选抠图失败:", error);
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toast.error(error instanceof Error ? error.message : `${actionName}失败`);
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} finally {
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setIsCreatingDetachedResultNode(false);
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setIsProcessing(false);
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resetBoxCutoutState();
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}
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}, [
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addNode,
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boxCutoutSelection,
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data.src,
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displayTitle,
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isProcessing,
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node.id,
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node.position.x,
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node.position.y,
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node.size.height,
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node.size.width,
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projectId,
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resetBoxCutoutState,
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updateNode,
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runCanvasRemoteOperation,
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]);
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const animateAddToChat = useCallback(async (previewUrl?: string) => {
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@ -4,6 +4,9 @@ import {
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executeRmbgJob,
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fetchImageBufferFromUrl,
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} from "@/lib/ai/rmbg/service";
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import { createLogger } from "@/lib/observability/logger";
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const logger = createLogger("box-cutout-service");
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export type NormalizedCropRect = {
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x: number;
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@ -13,6 +16,7 @@ export type NormalizedCropRect = {
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};
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export interface ExecuteBoxCutoutJobParams {
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requestId?: string;
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userId: string;
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imageUrl: string;
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cropRect: Partial<NormalizedCropRect>;
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@ -143,6 +147,7 @@ function applyPadding(
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export async function executeBoxCutoutJob(
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params: ExecuteBoxCutoutJobParams,
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): Promise<ExecuteBoxCutoutJobResult> {
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const requestId = params.requestId || crypto.randomUUID();
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const imageUrl = String(params.imageUrl || "").trim();
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if (!imageUrl) {
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throw new BoxCutoutServiceError("缺少 imageUrl 参数", 400);
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@ -150,7 +155,7 @@ export async function executeBoxCutoutJob(
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const cropRect = sanitizeNormalizedCropRect(params.cropRect);
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if (!cropRect) {
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throw new BoxCutoutServiceError("缺少有效的 cropRect 参数", 400);
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throw new BoxCutoutServiceError("框选范围无效，请重新框选需要抠出的区域后提交。", 400);
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}
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const paddingRatio = normalizeBoxCutoutPaddingRatio(params.paddingRatio);
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@ -170,7 +175,7 @@ export async function executeBoxCutoutJob(
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const cropRectPixels = toPixelRect(cropRect, sourceWidth, sourceHeight);
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if (cropRectPixels.width < MIN_CROP_EDGE_PX || cropRectPixels.height < MIN_CROP_EDGE_PX) {
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throw new BoxCutoutServiceError("框选区域过小，请重新框选", 400);
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throw new BoxCutoutServiceError("框选区域过小，宽、高均须至少 24 像素，请扩大框选范围后重新提交。", 400);
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}
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const paddedCropRect = applyPadding(cropRect, paddingRatio);
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@ -184,7 +189,18 @@ export async function executeBoxCutoutJob(
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})
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.toBuffer();
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logger.info("crop_prepared", {
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requestId,
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sourceNodeId: params.sourceNodeId,
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sourceWidth,
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sourceHeight,
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cropRectPixels,
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paddedCropRectPixels,
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inputBytes: croppedBuffer.length,
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});
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const result = await executeRmbgJob({
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requestId,
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userId: params.userId,
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imageBuffer: croppedBuffer,
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imageBase64: croppedBuffer.toString("base64"),
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@ -1,16 +1,15 @@
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import {
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executeBoxCutoutJob,
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} from "@/lib/ai/box-cutout/service";
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import { executeExtendJob } from "@/lib/ai/extend/service";
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import { executeLayerSplitJob } from "@/lib/ai/layer-split/service";
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import { executeResizeJob } from "@/lib/ai/resize/service";
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import {
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executeRmbgJob,
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fetchImageBufferFromUrl,
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RmbgServiceError,
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} from "@/lib/ai/rmbg/service";
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import type { CanvasCapabilityClientCommand } from "@/lib/canvas/capabilities/client-command";
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import type { CanvasCapabilityTarget } from "@/lib/canvas/capabilities/context";
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import { resolveCanvasRuntimeEndpoint } from "@/lib/canvas/capabilities/internal-endpoint";
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import { executeBoxCutoutPOST } from "@/lib/canvas/operations/box-cutout";
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import { generateCanvasImage } from "@/lib/canvas/generate-image";
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import { requestLongTaskResult } from "@/lib/client/long-task";
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import {
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@ -187,25 +186,35 @@ async function executeForTarget(
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}
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if (command.capabilityId === "image.box_cutout") {
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const result = await executeBoxCutoutJob({
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userId: params.userId,
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imageUrl: target.sourceImageUrl,
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sourceNodeId: target.nodeId,
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cropRect: {
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x: asFiniteNumber(command.args.x),
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y: asFiniteNumber(command.args.y),
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width: asFiniteNumber(command.args.width),
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height: asFiniteNumber(command.args.height),
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},
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paddingRatio: asFiniteNumber(command.args.paddingRatio),
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prompt: prompt || "框选抠图",
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});
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const response = await executeBoxCutoutPOST(new Request(params.requestUrl, {
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method: "POST",
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headers: { "Content-Type": "application/json", "X-Request-ID": command.requestId },
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body: JSON.stringify({
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imageUrl: target.sourceImageUrl,
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sourceNodeId: target.nodeId,
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cropRect: {
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x: asFiniteNumber(command.args.x),
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y: asFiniteNumber(command.args.y),
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width: asFiniteNumber(command.args.width),
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height: asFiniteNumber(command.args.height),
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},
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paddingRatio: asFiniteNumber(command.args.paddingRatio),
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prompt: prompt || "框选抠图",
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}),
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}), params.userId);
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const result = await response.json();
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if (!response.ok || !result.success) {
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throw new RmbgServiceError(result.detail || result.message || result.error || "框选抠图未能完成", response.status);
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}
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return [{
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...common,
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assetId: result.mediaAssetId || undefined,
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metadata: {
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editMode: "box-cutout",
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cropRectApplied: result.cropRectApplied,
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paddedCropRectApplied: result.paddedCropRectApplied,
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cropRectPixels: result.cropRectPixels,
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paddedCropRectPixels: result.paddedCropRectPixels,
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},
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title: `${target.title}-框选抠图`,
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url: result.original_url,
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96
lib/canvas/operations/box-cutout.ts
Normal file
96
lib/canvas/operations/box-cutout.ts
Normal file
@ -0,0 +1,96 @@
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import "server-only";
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import { NextResponse } from "next/server";
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import {
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BoxCutoutServiceError,
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executeBoxCutoutJob,
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} from "@/lib/ai/box-cutout/service";
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import { RmbgServiceError } from "@/lib/ai/rmbg/service";
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import { getPointsSystemConfig } from "@/lib/db/queries";
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import { prepareFeaturePointsCharge } from "@/lib/points/feature-charge";
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import { getImageToolCreditCost } from "@/lib/points/config";
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import { formatRequestFailure, getRequestFailureDetails } from "@/lib/request-error";
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type BoxCutoutRequest = {
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imageUrl?: string;
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cropRect?: {
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x?: number;
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y?: number;
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width?: number;
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height?: number;
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};
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paddingRatio?: number;
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prompt?: string;
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chatId?: string | null;
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messageId?: string | null;
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skipGallerySave?: boolean;
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sourceNodeId?: string;
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};
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export async function executeBoxCutoutPOST(request: Request, userId: string) {
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const requestId = request.headers.get("x-request-id") || crypto.randomUUID();
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try {
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if (!userId) {
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return NextResponse.json({ success: false, error: "未授权，请先登录" }, { status: 401 });
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}
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const body = (await request.json()) as BoxCutoutRequest;
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const rawImageUrl = String(body.imageUrl || "").trim();
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if (!rawImageUrl) {
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throw new BoxCutoutServiceError("缺少原图链接，请重新选择图片后提交。", 400);
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}
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const resolvedImageUrl = new URL(rawImageUrl, request.url).toString();
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const pointsConfig = await getPointsSystemConfig();
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const pointsCharge = await prepareFeaturePointsCharge({
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userId,
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unitCost: getImageToolCreditCost(pointsConfig, "box-cutout"),
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reason: "image_box_cutout",
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modelId: "box-cutout",
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note: "框选抠图消耗积分",
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pointsConfig,
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});
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if (!pointsCharge.ok) {
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return NextResponse.json(pointsCharge.payload, { status: pointsCharge.status });
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}
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const result = await executeBoxCutoutJob({
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requestId,
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userId,
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imageUrl: resolvedImageUrl,
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cropRect: body.cropRect || {},
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paddingRatio: body.paddingRatio,
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prompt: body.prompt || "框选抠图",
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chatId: body.chatId || null,
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messageId: body.messageId || null,
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skipGallerySave: body.skipGallerySave === true,
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sourceNodeId: body.sourceNodeId,
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});
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if (pointsCharge.chargeable) {
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try {
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await pointsCharge.consume();
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} catch (pointsError) {
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console.error("[Points] Failed to consume box cutout points:", pointsError);
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}
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}
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return NextResponse.json({ ...result, requestId });
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} catch (error) {
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const failure = getRequestFailureDetails(error, "框选抠图未能完成");
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const payload = {
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success: false,
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error: formatRequestFailure(failure, requestId),
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detail: error instanceof Error ? error.message : "框选抠图未能完成",
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code: failure.code,
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failure,
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requestId,
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};
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if (error instanceof BoxCutoutServiceError || error instanceof RmbgServiceError) {
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||||
return NextResponse.json(payload, { status: error.status });
|
||||
}
|
||||
|
||||
console.error("[BoxCutout] 处理失败:", error);
|
||||
return NextResponse.json(payload, { status: 500 });
|
||||
}
|
||||
}
|
||||
@ -102,7 +102,7 @@ test("mixed-model batches bill and label only the delivered images using their a
|
||||
test("headless image features cannot substitute their default when a pinned model disappears", async () => {
|
||||
let generated = 0;
|
||||
const mocks: Record<string, any> = {
|
||||
"@/lib/ai/box-cutout/service": {}, "@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {}, "@/lib/ai/rmbg/service": {},
|
||||
"@/lib/canvas/operations/box-cutout": {}, "@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {}, "@/lib/ai/rmbg/service": {},
|
||||
"@/lib/canvas/capabilities/internal-endpoint": {}, "@/lib/client/long-task": {},
|
||||
"@/lib/canvas/generate-image": { generateCanvasImage: async () => { generated++; return { images: [] }; } },
|
||||
"@/lib/style-pro/model-options": { getStyleProImageModelEntries: async () => [{ model: { id: "default", modelId: "default", isDefault: true } }], sortStyleProImageModelEntries: (entries: any[]) => entries, findStyleProImageModelByRef: () => null },
|
||||
|
||||
@ -103,6 +103,33 @@ test("a recovered matting rejection shows its dimensions and advice without chan
|
||||
expect(useCanvasStore.getState().canvasRevision).toBe("r1");
|
||||
});
|
||||
|
||||
test("a lost box-cutout response recovers the same selection into its original canvas with one submission", async () => {
|
||||
const submitted = createCanvasCapabilityClientCommand({ projectId: "project-a", capabilityId: "image.box_cutout", nodeIds: ["source"], source: "toolbar", args: { x: 0.25, y: 0.2, width: 0.4, height: 0.5, paddingRatio: 0.08 } });
|
||||
let posts = 0, polls = 0;
|
||||
const selected = { ...node("cutout"), data: { src: "https://example.com/cutout.png", metadata: { editMode: "box-cutout", cropRectApplied: submitted.args } } };
|
||||
globalThis.fetch = (async (url, options) => {
|
||||
if (options?.method === "POST") {
|
||||
posts++;
|
||||
expect(JSON.parse(String(options.body))).toMatchObject({ capabilityId: "image.box_cutout", requestId: submitted.requestId, args: submitted.args });
|
||||
useCanvasStore.getState().moveNode("source", { x: 20, y: 30 });
|
||||
return new Response(null, { status: 524 });
|
||||
}
|
||||
if (String(url).includes("/capabilities?")) {
|
||||
polls++;
|
||||
expect(String(url)).toContain(encodeURIComponent(submitted.requestId));
|
||||
return Response.json({ success: true, task: { status: "succeeded" } });
|
||||
}
|
||||
return Response.json({ success: true, data: { updatedAt: "r2", canvasData: { nodes: [node("source"), selected], edges: [] } } });
|
||||
}) as typeof fetch;
|
||||
await executeCanvasToolbarCapability(submitted);
|
||||
expect({ posts, polls }).toEqual({ posts: 1, polls: 1 });
|
||||
const state = useCanvasStore.getState();
|
||||
expect(state.projectId).toBe("project-a");
|
||||
expect(state.nodes.map(n => n.id)).toEqual(["source", "cutout"]);
|
||||
expect(state.nodes[0].position).toEqual({ x: 20, y: 30 });
|
||||
expect(state.nodes[1].data).toEqual(selected.data);
|
||||
});
|
||||
|
||||
test("switching projects during processing does not load the old result into the new project", async () => {
|
||||
globalThis.fetch = (async (url) => {
|
||||
if (String(url).endsWith("/capabilities")) {
|
||||
|
||||
@ -5,6 +5,91 @@ import { getRequestFailureDetails } from "@/lib/request-error";
|
||||
|
||||
const cdn = "https://scqnycdn.jiansun.vip";
|
||||
|
||||
test("box cutout submits exactly the padded selection and keeps the original URL as provenance", async () => {
|
||||
const pixels = Buffer.alloc(120 * 80 * 3);
|
||||
for (let y = 0; y < 80; y++) for (let x = 0; x < 120; x++) {
|
||||
const offset = (y * 120 + x) * 3;
|
||||
pixels[offset] = x * 2; pixels[offset + 1] = y * 3; pixels[offset + 2] = x + y;
|
||||
}
|
||||
const original = await sharp(pixels, { raw: { width: 120, height: 80, channels: 3 } }).png().toBuffer();
|
||||
let submitted: any;
|
||||
const box = serverLoader({
|
||||
"@/lib/ai/rmbg/service": {
|
||||
fetchImageBufferFromUrl: async () => original,
|
||||
executeRmbgJob: async (params: any) => { submitted = params; return { original_url: `${cdn}/selected.png` }; },
|
||||
},
|
||||
})("lib/ai/box-cutout/service.ts");
|
||||
const result = await box.executeBoxCutoutJob({ userId: "user-a", requestId: "box-a", sourceNodeId: "source", imageUrl: `${cdn}/original.png`, cropRect: { x: 0.25, y: 0.25, width: 0.5, height: 0.5 }, paddingRatio: 0.1 });
|
||||
expect(result.cropRectPixels).toEqual({ left: 30, top: 20, width: 60, height: 40 });
|
||||
expect(result.paddedCropRectPixels).toEqual({ left: 24, top: 16, width: 72, height: 48 });
|
||||
expect(submitted).toMatchObject({ requestId: "box-a", sourceImageUrl: `${cdn}/original.png` });
|
||||
expect(submitted.inputImageUrl).toBeUndefined();
|
||||
const expected = await sharp(original).extract(result.paddedCropRectPixels).raw().toBuffer();
|
||||
expect((await sharp(submitted.imageBuffer).raw().toBuffer()).equals(expected)).toBe(true);
|
||||
});
|
||||
|
||||
test("box cutout shares the configured charge once after success and never charges a rejected input", async () => {
|
||||
class InputError extends Error { status = 400; }
|
||||
for (const rejected of [false, true]) {
|
||||
let creates = 0, charges = 0;
|
||||
const operation = serverLoader({
|
||||
"@/lib/ai/box-cutout/service": { BoxCutoutServiceError: InputError, executeBoxCutoutJob: async (params: any) => {
|
||||
creates++;
|
||||
expect(params.requestId).toBe("box-a");
|
||||
if (rejected) throw new InputError("抠图参考图分辨率超限（5000×3000 像素），当前 AOS 上游要求宽、高均不超过 4096 像素。");
|
||||
return { success: true, original_url: `${cdn}/selected.png` };
|
||||
} },
|
||||
"@/lib/ai/rmbg/service": { RmbgServiceError: InputError },
|
||||
"@/lib/db/queries": { getPointsSystemConfig: async () => ({ enabled: true, creditCostPerImageBoxCutout: 7 }) },
|
||||
"@/lib/points/feature-charge": { prepareFeaturePointsCharge: async (params: any) => {
|
||||
expect(params).toMatchObject({ userId: "user-a", unitCost: 7, reason: "image_box_cutout", modelId: "box-cutout" });
|
||||
return { ok: true, chargeable: true, consume: async () => { charges++; } };
|
||||
} },
|
||||
})("lib/canvas/operations/box-cutout.ts");
|
||||
const response = await operation.executeBoxCutoutPOST(new Request("https://example.com/api/canvas/box-cutout", { method: "POST", headers: { "Content-Type": "application/json", "X-Request-ID": "box-a" }, body: JSON.stringify({ imageUrl: `${cdn}/original.png`, cropRect: { x: 0, y: 0, width: 0.5, height: 0.5 } }) }), "user-a");
|
||||
const result = await response.json();
|
||||
expect({ creates, charges }).toEqual({ creates: 1, charges: rejected ? 0 : 1 });
|
||||
expect(response.status).toBe(rejected ? 400 : 200);
|
||||
if (rejected) {
|
||||
expect(result.failure).toMatchObject({ code: "RMBG_INPUT_RESOLUTION_EXCEEDED", outcome: "failed" });
|
||||
expect(result.error).toContain("5000×3000");
|
||||
expect(result.error).toContain("本次未提交上游抠图任务");
|
||||
expect(result.error).toContain("请求编号：box-a");
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
test("headless box cutout keeps its task identity, pixel bounds and input-rejection status", async () => {
|
||||
class InputError extends Error {
|
||||
status: number;
|
||||
constructor(message: string, status: number) { super(message); this.status = status; }
|
||||
}
|
||||
let calls = 0;
|
||||
let rejectInput = false;
|
||||
const bounds = { left: 20, top: 30, width: 200, height: 300 };
|
||||
const executor = serverLoader({
|
||||
"@/lib/canvas/operations/box-cutout": { executeBoxCutoutPOST: async (request: Request, userId: string) => {
|
||||
calls++;
|
||||
expect(userId).toBe("user-a");
|
||||
expect(request.headers.get("x-request-id")).toBe("box-a");
|
||||
expect(await request.json()).toMatchObject({ sourceNodeId: "source", cropRect: { x: 0.1, y: 0.2, width: 0.3, height: 0.4 }, paddingRatio: 0.08 });
|
||||
return rejectInput ? Response.json({ success: false, detail: "抠图参考图分辨率超限（5000×3000 像素）" }, { status: 400 })
|
||||
: Response.json({ success: true, original_url: `${cdn}/cutout.png`, paddedCropRectPixels: bounds });
|
||||
} },
|
||||
"@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {},
|
||||
"@/lib/ai/rmbg/service": { RmbgServiceError: InputError },
|
||||
"@/lib/canvas/capabilities/internal-endpoint": {}, "@/lib/client/long-task": {},
|
||||
"@/lib/canvas/generate-image": {}, "@/lib/style-pro/model-options": {},
|
||||
})("lib/canvas/capabilities/headless-executor.ts");
|
||||
const params = { userId: "user-a", requestUrl: "https://example.com/api/canvas/project-a/capabilities", requestHeaders: new Headers(), command: { requestId: "box-a", capabilityId: "image.box_cutout", args: { x: 0.1, y: 0.2, width: 0.3, height: 0.4, paddingRatio: 0.08 } }, targets: [{ nodeId: "source", title: "原图", sourceImageUrl: `${cdn}/original.png` }] };
|
||||
const results = await executor.executeCanvasCapabilityHeadlessly(params);
|
||||
expect(calls).toBe(1);
|
||||
expect(results).toMatchObject([{ sourceNodeId: "source", url: `${cdn}/cutout.png`, metadata: { editMode: "box-cutout", paddedCropRectPixels: bounds } }]);
|
||||
rejectInput = true;
|
||||
await expect(executor.executeCanvasCapabilityHeadlessly(params)).rejects.toMatchObject({ status: 400 });
|
||||
expect(calls).toBe(2);
|
||||
});
|
||||
|
||||
function rmbgLoader(fetch: typeof globalThis.fetch, timer?: typeof setTimeout) {
|
||||
return serverLoader({
|
||||
"@/lib/db/queries": { getSystemSetting: async () => ({ value: { provider: "aoscdn", aosApiKey: "test-key" } }) },
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user